The ability to assess risk is important in the context of financial lending. A defaulted loan or a delinquent loan is costly to the owner of the asset (initially the lender). As a lender improves its ability to determine risk associated with a loan, it can make better underwriting and pricing decisions that will result in fewer loans that default or become delinquent. In the secondary mortgage market, where mortgage loans are commonly sold to investors, fewer defaulted/delinquent loans results in a better return on investment, resulting in increased capital flow to the housing market. Even for loans that have already been made to a borrower, better risk predictions allow more effective risk management strategies to be employed (e.g., more effective hedging or workout strategies) and, therefore, decrease vulnerability to defaults/delinquencies. Better risk predictions, therefore, decrease the defaults/delinquencies, improve capital flow to the housing market, and ultimately decrease mortgage costs for consumers.
In the past, lending institutions, such as banks, have assessed loan risk using credit reports and/or credit scores. Credit reports are records sent from a credit reporting agency to prospective lenders, employers, and insurers that provide information about the credit standing of a consumer. Credit reporting agencies are companies that gather the information about consumers and sell it to creditors and/or employers and/or insurers. A credit score often refers to a number generated by a statistical model that is used to objectively evaluate the credit worthiness of the borrower(s) relevant to making a credit decision.
A large number of factors may be used to assess risk associated with a loan, including borrower-specific risk factors, loan-specific risk factors, and property/collateral-specific risk factors. Borrower-specific risk factors may include factors such as the borrower's credit score as mentioned above, as well as other factors such as the borrower's income and financial reserves. Property-specific risk factors may include factors such as whether the property is owner-occupied. Loan-specific risk factors may include factors such as the loan-to-value ratio, the loan amount, the loan purpose, and so on.
Loans are commonly sold in the secondary mortgage market shortly after the loan is made to the borrower (e.g., within a few months). Sometimes, loans are sold years later, usually as part of the sale of a group of loans. Determining risk of delinquency or default in this situation can be problematic, though, because data about the borrower may not be available. For example, for mortgage loans originated prior to late 1996, it was common for lenders to not obtain credit scores (e.g., FICO scores) for borrowers. As such, loan data sets for loans originated prior to late 1996 are often missing credit score data. As previously indicated, credit scores are an important predictor of delinquency/default. While it would be possible to supplement the loan data set with the borrower's current credit score, borrower consent is typically required to obtain such information, making this approach impractical. Likewise, other types of information, such as reserves (assets at origination relative to the monthly mortgage payment) and backend ratio (monthly debt payment relative to monthly income) are often also missing. So, while certain historical information may be correlated with default behavior, if the values are missing, it is difficult to determine the underlying risk of default for the loan.
Thus, there is a need for an improved method and system that provides a measure of loan credit risk and performance (e.g., the probability of delinquency or default of a loan). Further, there is a need to provide a comprehensive summary of many risk factors observed at loan acquisition combining the risk characteristics of borrower, property, loan, and other factors. Even further, there is a need to provide the above information in situations where information about some of the key variables is missing in the historical data.
Furthermore, in making risk assessments or conducting other loan performance analysis, a lending institution or other organization may choose to evaluate the performance of a particular group of loans relative to the performance of another group of loans. For example, the lending institution may desire to evaluate the performance of a newly created loan product and/or loans that are still in the early stages of repayment (e.g., loans that are still in the first or second year of repayment). The particular group of loans to be evaluated might include, e.g., loans from a particular lender, loans serviced by a particular loan servicer, or loans with the same or similar product characteristics. Because only a minimal amount of payment history has been compiled, it is often desirable for the lending institution to characterize the performance of this particular group of loans relative to the performance of a comparable group of loans with known payment history. The results of the comparison may then be used, for example, to assess and manage risk associated with the particular group of loans, or to make proper adjustment in the underwriting and pricing policies.
However, in making such a performance comparison, it is important to establish an appropriate benchmark to which a meaningful comparison can be made. For example, it may not be appropriate to compare the performance of a grouping of new loans from a particular lender who deals primarily with high-risk loans with the overall performance of an entire loan portfolio where that portfolio contains loans from a variety of lenders who may or may not deal in high risk loans. It is desirable to ensure that a meaningful comparison is made between the particular group of loans to be evaluated and the comparable group of loans. Additionally, it is also desirable to evaluate the statistical significance of any discrepancy in performance between the particular grouping of loans being evaluated and the comparable grouping of loans.
Further, in the context of financial lending, it is often desirable to have access to a means for making a meaningful comparison between different groups of loans and evaluating the statistical significance of any resulting discrepancies in loan performance that is easy to use and does not require an advanced knowledge of statistical theory. There is also need for an improved method and system for assessing the performance of a particular group of loans with respect to the performance of another comparable group of loans which provides a test statistic that is easy to characterize.
In addition, methodologies employed in making the loan performance comparison may sometimes provide inaccurate results if the loans in the particular group of loans to be evaluated are also included in the comparable group of loans. For example, a lending institution may desire to evaluate the performance of a grouping of a specific type of loan consisting of only those loans of that specific type that are still in the early stages of repayment (e.g., loans that are still in the first or second year of repayment) relative to a comparable group of loans comprising all loans of that specific type. Where very few of the loans in the comparable group have known payment history beyond the first or second year, the comparative analysis essentially operates to compare the performance of the particular group being evaluated with itself. Thus, there is need for an improved method and system for assessing the performance of a particular group of loans with respect to the performance of another comparable group of loans which makes it possible to avoid inaccuracies created when the study group is too dominant of a factor in the control group. In addition, there is further need for an improved method and system for assessing the performance of a particular study group of loans with respect to the performance of another comparable group of loans, wherein the comparable group of loans may either include or exclude the loans in the study group.